Shape memory polymers (SMP) are smart materials that can recover their original shape from a deformed state under external stimuli. SMPs generally consist of crosslinked polymer networks that determine the permanent shape of the material, and switching segments that are capable of being oriented and solidified to fix a temporary shape. The shape recovery is driven by the entropic force of the switching domains, which tend to gain entropy and return to the random conformation during phase transitions, such as glass transition, liquid crystalline (LC) transition, and melting transition.
Powered by the reversible LC phase transition and the unique coupling between LC mesogens and polymer networks, liquid crystalline elastomers (LCE) represent a special class of SMPs. They exhibit reversible shape change upon the application of external stimuli, such as heat, light, and magnetic field, which makes them excellent candidates for artificial muscles, sensors, and lithography substrates. The importance of LCEs has been realized in their great potential for a wide variety of applications ranging from biomedical (e.g., biosensors, drug delivery systems, and intelligent implants) to aerospace engineering (e.g., packing materials, morphing structures, and self-assembling devices). A number of LCEs with different LC phases and network structures have been synthesized and characterized. These materials exhibit a wide variety of shape memory and actuating behaviors.
However, despite their interesting properties and remarkable potential, practical applications of LCEs are limited due to the difficulties in tailoring thermal transition temperatures and thermomechanical properties of the materials for rendering them specifically useful in additive manufacturing applications. Thus, there would be a significant benefit in LCEs in which such properties are tailored, particularly for use in additive manufacturing processes.